`i'ddZddlmZddlmZejeZGddeZdgZ dS)zBamba model configuration)PretrainedConfig)loggingc|eZdZdZdZdgZ dfd ZedZxZ S) BambaConfiga This is the configuration class to store the configuration of a [`BambaModel`]. It is used to instantiate a BambaModel model according to the specified arguments, defining the model architecture. Instantiating a configuration with defaults taken from [ibm-fms/Bamba-9.8b-2.2T-hf](https://huggingface.co/ibm-fms/Bamba-9.8b-2.2T-hf). The BambaModel is a hybrid [mamba2](https://github.com/state-spaces/mamba) architecture with SwiGLU. The checkpoints are jointly trained by IBM, Princeton, and UIUC. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: vocab_size (`int`, *optional*, defaults to 128000): Vocabulary size of the Bamba model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`BambaModel`] tie_word_embeddings (`bool`, *optional*, defaults to `False`): Whether the model's input and output word embeddings should be tied. Note that this is only relevant if the model has an output word embedding layer. hidden_size (`int`, *optional*, defaults to 4096): Dimension of the hidden representations. intermediate_size (`int`, *optional*, defaults to 14336): Dimension of the MLP representations. num_hidden_layers (`int`, *optional*, defaults to 32): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 32): Number of attention heads for each attention layer in the Transformer encoder. num_key_value_heads (`int`, *optional*, defaults to 8): This is the number of key_value heads that should be used to implement Grouped Query Attention. If `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if `num_key_value_heads=1` the model will use Multi Query Attention (MQA) otherwise GQA is used. When converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed by meanpooling all the original heads within that group. For more details, check out [this paper](https://huggingface.co/papers/2305.13245). If it is not specified, will default to `8`. hidden_act (`str` or `function`, *optional*, defaults to `"silu"`): The non-linear activation function (function or string) in the decoder. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. rms_norm_eps (`float`, *optional*, defaults to 1e-05): The epsilon used by the rms normalization layers. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). Only relevant if `config.is_decoder=True`. num_logits_to_keep (`int` or `None`, *optional*, defaults to 1): Number of prompt logits to calculate during generation. If `None`, all logits will be calculated. If an integer value, only last `num_logits_to_keep` logits will be calculated. Default is 1 because only the logits of the last prompt token are needed for generation. For long sequences, the logits for the entire sequence may use a lot of memory so, setting `num_logits_to_keep=1` will reduce memory footprint significantly. pad_token_id (`int`, *optional*, defaults to 0): The id of the padding token. bos_token_id (`int`, *optional*, defaults to 1): The id of the "beginning-of-sequence" token. eos_token_id (`int`, *optional*, defaults to 2): The id of the "end-of-sequence" token. max_position_embeddings (`int`, *optional*, defaults to 262144): Max cached sequence length for the model attention_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. attn_layer_indices (`list`, *optional*): Specifies the layer indices that will have full attention. Must contain values at most num_hidden_layers. mamba_n_heads (`int`, *optional*, defaults to 128): The number of mamba heads used in the v2 implementation. mamba_d_head (`int`, *optional*, defaults to `"auto"`): Head embedding dimension size mamba_n_groups (`int`, *optional*, defaults to 1): The number of the mamba groups used in the v2 implementation. mamba_d_state (`int`, *optional*, defaults to 256): The dimension the mamba state space latents mamba_d_conv (`int`, *optional*, defaults to 4): The size of the mamba convolution kernel mamba_expand (`int`, *optional*, defaults to 2): Expanding factor (relative to hidden_size) used to determine the mamba intermediate size mamba_chunk_size (`int`, *optional*, defaults to 256): The chunks in which to break the sequence when doing prefill/training mamba_conv_bias (`bool`, *optional*, defaults to `True`): Flag indicating whether or not to use bias in the convolution layer of the mamba mixer block. mamba_proj_bias (`bool`, *optional*, defaults to `False`): Flag indicating whether or not to use bias in the input and output projections (["in_proj", "out_proj"]) of the mamba mixer block z_loss_coefficient (`float`, *optional*, defaults to 0.0): Coefficient for auxiliary z-loss used to control logit growth during training bambapast_key_valuesF8 silu{Gz?h㈵>TNautoc p||_||_||_||_||_||_||_||_d|_d|_ ||}||_ ||_ | |_ | |_ | |_| |_||_d|_d|_d|_||z}||zdkrt)d|dkr||z}||z|krt)d||_||_||_||_||_||_||_||_||_||_t?j d | |||d|dS) NFg@g?rz4mamba_n_heads must divide mamba_expand * hidden_sizerzPThe dimensions for the Mamba head state do not match the model intermediate_size) pad_token_id bos_token_id eos_token_idtie_word_embeddings)! vocab_sizer hidden_sizeintermediate_sizenum_hidden_layersnum_attention_headsmax_position_embeddingsattention_dropoutattention_biasmlp_biasnum_key_value_heads hidden_actinitializer_range rms_norm_eps use_cachenum_logits_to_keepattn_layer_indices rope_theta rope_scalingpartial_rotary_factor ValueError mamba_n_heads mamba_d_headmamba_n_groups mamba_d_state mamba_d_conv mamba_expandmamba_chunk_sizemamba_conv_biasmamba_proj_biasz_loss_coefficientsuper__init__) selfr rr!r"r#r$r)r*r+r,r-r.rrrr%r&r/r4r5r6r7r8r9r:r;r<r=kwargsmamba_intermediate __class__s /home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/transformers/models/bamba/configuration_bamba.pyr?zBambaConfig.__init__os@%#6 &!2!2#6 '>$!2#   &"5 #6 $!2(""4"4! %(")K7  - 2 2STT T 6 ! !->L - '+= = =opp p*(,*(( 0.."4 %%% 3         cDfdtjDS)Nc8g|]}jr |jvrdndS) attentionmamba)r/).0ir@s rD z1BambaConfig.layers_block_type..sC   !3 bT=T8T8TKK[b   rE)ranger#)r@s`rDlayers_block_typezBambaConfig.layers_block_types9    4122    rE)r Fr r r r r rrrTrrrrrrNrrrrrrrTFr) __name__ __module__ __qualname____doc__ model_typekeys_to_ignore_at_inferencer?propertyrN __classcell__)rCs@rDrrsQQfJ#4"5! &;Y Y Y Y Y Y v  X     rErN) rRconfiguration_utilsrutilsr get_loggerrOloggerr__all__rrErDr\s 333333  H % %w w w w w "w w w t /rE